We describe a Big Data-practical, SQL-implementable algorithm for efficiently determining connected components for graph data stored in a Massively Parallel Processing (MPP) relational database. The algorithm described is a linear-space, randomised algorithm, always terminating with the correct answer but subject to a stochastic running time, such that for any ǫ > 0 and any input graph G = 〈V,E...

This paper presents two new strategies that can be used to greatly improve the speed of connected component labeling algorithms. To assign a label to a new object, most labeling algorithms use a scanning step that examines some of its neighbors. The first strategy exploits the dependencies among the neighbors to reduce the number of neighbors examined. When considering 8-connected components in...

Connected component labeling (CCL) is a task of detecting connected regions in input data, and it finds its applications in pattern recognition, computer vision, and image processing. We present a new algorithm for connected component labeling in 2-D images implemented in CUDA. We first provide a brief overview of the CCL problem together with existing CPU-oriented algorithms. The rest of the c...

A. Csaszar introduced and extensively studied the notion of generalized open sets. Following Csazar, we introduce a new notion hyperconnected. We study some specic properties about connected and hyperconnected in generalized topological spaces. Finally, we characterize the connected component in generalized topological spaces.